This paper describes follow-up for a cohort of 4530 residents living in the asbestos manufacturing community of Ambler, PA, U.S. in 1930. Using re-identified census data, cause and date of death data obtained from the genealogic website Ancestry.com, along with geospatial analysis, we explored relationships among demographic characteristics, occupational, paraoccupational and environmental asbestos exposures. We identified death data for 2430/4530 individuals. Exposure differed significantly according to race, gender, age, and recency of immigration to the U.S. Notably, there was a significant difference in the availability of year of death information for non-white vs. white individuals (odds ratio (OR) = 0.62 p-value < 0.001), females (OR = 0.53, p-value < 0.001), first-generation immigrants (OR = 0.67, p-value = 0.001), second-generation immigrants (OR = 0.31, p-value < 0.001) vs. non-immigrants, individuals aged less than 20 (OR = 0.31 p-value < 0.001) and individuals aged 20 to 59 (OR = 0.63, p-value < 0.001) vs. older individuals. Similarly, the cause of death was less often available for non-white individuals (OR = 0.42, p-value <0.001), first-generation immigrants and (OR = 0.71, p-value = 0.009), second-generation immigrants (OR = 0.49, p-value < 0.001), individuals aged less than 20 (OR = 0.028 p-value < 0.001), and individuals aged 20 to 59 (OR = 0.26, p-value < 0.001). These results identified ascertainment bias that is important to consider in analyses that investigate occupational, para-occupational and environmental asbestos exposure as risk factors for mortality in this historic cohort. While this study attempts to describe methods for assessing itemized asbestos exposure profiles for a community in 1930 using Ancestry.com and other publicly accessible databases, it also highlights how historic cohort studies likely underestimate the impact of asbestos exposure on vulnerable populations. Future work will aim to assess mortality patterns in this cohort.
Keywords: asbestos; asbestos related diseases; ascertainment bias; health disparities; historic cohort.